Epidemiological Assessment of African Swine Fever Spread in the Dominican Republic.

Since African Swine Fever (ASF) was detected in the Dominican Republic in July 2021, it has negatively impacted the country's swine industry. Assessing the epidemiological situation is crucial to helping local authorities and industry stakeholders control the disease. Here, data on 155 reported outbreaks in the Dominican Republic from November 2022 to June 2023 were evaluated. Descriptive spatiotemporal analysis was performed to characterize disease distribution and spread, and between-herd R0 was calculated for the study period. The Knox test and a space-time permutation model were used to evaluate clustering. Data on clinical presentation, biosecurity measures, and suspected reasons for introduction were categorized and summarized. The majority (78%) of outbreaks occurred on backyard farms which generally had low biosecurity. Across farm types, the majority of pigs were still alive at the time of depopulation. Spatiotemporal findings and R0 estimates suggest an endemic pattern of disease geographically located centrally within the country. Clustering was detected even at small temporal and spatial distances due to outbreaks amongst neighboring backyard farms. These results provide critical information on the current state of the ASF epidemic in the Dominican Republic and will aid government officials and swine industry leaders in developing effective ASF control strategies.

Factors Affecting the Spread, Diagnosis, and Control of African Swine Fever in the Philippines.

African Swine Fever (ASF) is a highly contagious disease that threatens the swine industry globally. Since its introduction into the Philippines in 2019, ASF has spread extensively in both commercial and backyard farms. Here, using a mix of qualitative and quantitative methods, including conjoint and SWOT analyses, world café discussions, and multivariable regression models, the most important factors that influence the spread, diagnosis, and control of ASF in the Philippines were identified. Research findings suggest that swill or contaminated feed, inadequate biosecurity protocols, and movement of personnel were the top risk factors favoring ASF spread among farms in general. For commercial farms, contaminated vehicles and personnel were also important, whereas for backyard farms, the introduction of new pigs, environmental contamination, and poor feeding quality were relevant risk factors. Notable clinical signs of ASF in pigs include reduced feed intake, huddled behavior, and reluctance to stand. This study highlights the need for timely reporting, trust-building initiatives, and enhanced biosecurity measures to effectively manage ASF outbreaks in the country. Results here contribute to the knowledge of factors affecting ASF spread in the Philippines and can help design prevention and control measures in ASF-infected countries while enhancing preparedness in countries free from the disease.

Modeling the accuracy of a novel PCR and antibody ELISA for African swine fever virus detection using Bayesian latent class analysis.

Introduction: Diagnostic test evaluation for African swine fever (ASF) in field settings like Vietnam is critical to understanding test application in intended populations for surveillance and control strategies. Bayesian latent class analysis (BLCA) uses the results of multiple imperfect tests applied to an individual of unknown disease status to estimate the diagnostic sensitivity and specificity of each test, forgoing the need for a reference test. Methods: Here, we estimated and compared the diagnostic sensitivity and specificity of a novel indirect ELISA (iELISA) for ASF virus p30 antibody (Innoceleris LLC.) and the VetAlert™ ASF virus DNA Test Kit (qPCR, Tetracore Inc.) in field samples from Vietnam by assuming that disease status 1) is known and 2) is unknown using a BLCA model. In this cross-sectional study, 398 paired, individual swine serum/oral fluid (OF) samples were collected from 30 acutely ASF-affected farms, 37 chronically ASF-affected farms, and 20 ASF-unaffected farms in Vietnam. Samples were tested using both diagnostic assays. Diagnostic sensitivity was calculated assuming samples from ASF-affected farms were true positives and diagnostic sensitivity by assuming samples from unaffected farms were true negatives. ROC curves were plotted and AUC calculated for each test/sample combination. For comparison, a conditionally dependent, four test/sample combination, three population BLCA model was fit. Results: When considering all assumed ASF-affected samples, qPCR sensitivity was higher for serum (65.2%, 95% Confidence Interval [CI] 58.1-71.8) and OF (52%, 95%CI 44.8-59.2) compared to the iELISA (serum: 42.9%, 95%CI 35.9-50.1; OF: 33.3%, 95%CI 26.8-40.4). qPCR-serum had the highest AUC (0.895, 95%CI 0.863-0.928). BLCA estimates were nearly identical to those obtained when assuming disease status and were robust to changes in priors. qPCR sensitivity was considerably higher than ELISA in the acutely-affected population, while ELISA sensitivity was higher in the chronically-affected population. Specificity was nearly perfect for all test/sample types. Discussion: The effect of disease chronicity on sensitivity and specificity could not be well characterized here due to limited data, but future studies should aim to elucidate these trends to understand the best use of virus and antibody detection methods for ASF. Results presented here will help the design of surveillance and control strategies in Vietnam and other countries affected by ASF.

Enhancing passive surveillance for African swine fever detection on U.S. swine farms.

As the threat of African swine fever (ASF) introduction into new areas continues, animal health officials and epidemiologists need novel tools for early detection and surveillance. Passive surveillance from swine producers and veterinarians is critical to identify cases, especially the first introduction. Enhanced passive surveillance (EPS) protocols are needed that maximize temporal sensitivity for early ASF detection yet are easily implemented. Regularly collected production and disease data on swine farms may pose an opportunity for developing EPS protocols. To better understand the types of data regularly collected on swine farms and on-farm disease surveillance, a questionnaire was distributed in summer 2022 across multiple channels to MN swine producers. Thirty responses were received that indicated the majority of farms collect various types of disease information and conduct routine diagnostic testing for endemic swine diseases. Following this, a focus group discussion was held at the 2022 Leman Swine Conference where private and public stakeholders discussed the potential value of EPS, opportunities for collaboration, and challenges. The reported value of EPS varied by stakeholder group, but generally participants felt that for swine producers and packers, EPS would help identify abnormal disease occurrences. Many opportunities were identified for collaboration with ongoing industry initiatives and swine management software. Challenges included maintaining motivation for participation in ASF-free areas, labor, data sharing issues, and the cost of diagnostic testing. These highlight important issues to address, and future collaborations can help in the development of practical, fit-for-purpose, and valuable EPS protocols for ASF detection in the swine industry.

A qualitative assessment of alternative eradication strategies for African swine fever in the Dominican Republic.

Since its recent detection in July 2021, the reintroduction of African swine fever (ASF) in the Dominican Republic (DR) has generated much discourse on various measures for its effective control. Strategies range from complete depopulation of the swine population, as was done in 1978, to a system of passive surveillance with endemicity, with many in-between. Currently, ASF-decision makers need a peer evaluation and comparison and contrast of these potential strategies that incorporates both private and public perspectives. To achieve this, we used strengths, weaknesses, opportunities, and threats (SWOT) analysis to evaluate three different theoretical ASF control scenarios with the aim of contributing evaluations of alternatives strategies to mitigate the epidemic's impact. These included total depopulation of all pigs in the DR, partial depopulation, and continuation of current control measures. Relevant experts from the DR private swine industry were identified through "snowball sampling" techniques. Five experts completed the SWOT questionnaire and additional questions considering aspects of financial cost, social impact, feasibility, animal welfare, and regional policy. The summarized responses were presented to the full group of experts initially nominated for final review and later to representatives of the DR government. The SWOT analysis highlighted that although there are certain benefits associated with each of the proposed strategies, there are also important drawbacks and disadvantages for all. This analysis is a tool for facilitating cooperating between the private-public industries, and ultimately it supports the development of strategies that will reduce ASF burden in the DR in a way suitable for all relevant stakeholders.

Rethinking the uncertainty of African swine fever virus contamination in feed ingredients and risk of introduction into the United States.

Economically relevant pathogens, such as African swine fever virus (ASFV), have been shown to survive when experimentally inoculated in some feed ingredients under the environmental conditions in transoceanic transport models. However, these models did not characterize the likelihood of virus survival under various time and temperature processes that feed ingredients undergo before they are added to swine diets. Here, we developed a quantitative risk assessment model to estimate the probability that one or more corn or soybean meal ocean vessels (25,000 tonnes) contaminated with ASFV would be imported into the United States annually. This final probability estimate was conditionally based on five likelihoods: the probability of initial ASFV contamination (p0), ASFV inactivation during processing (p1) and transport (p2), recontamination (pR), and ASFV inactivation while awaiting customs clearance at United States entry (p3). The probability of ASFV inactivation was modelled using corn and soybean (extruded or solvent extracted) processing conditions (times and temperatures), D-values (time to reduce 90% or 1-log) estimated from studies of ASFV thermal inactivation in pork serum (p1), and survival in feed ingredients during transoceanic transport (p2 and p3). 'What-if' scenarios using deterministic values for p0 and pR (1%, 10%, 25%, 50%, 75%, and 100%) were used to explore their impact on risk. The model estimated complete inactivation of ASFV after extrusion or solvent extraction processes regardless of the initial ASFV contamination probability assumed. The value of recontamination (ranging from 1% to 75%) was highly influential on the risk of one ASFV-contaminated soybean meal vessel entering the United States. Median risk estimates ranged from 0.064% [0.006%-0.60%; 95% probability interval (PI)], assuming a pR of 1.0%, up to 4.67% (0.45%-36.50% 95% PI) assuming a pR of 75.0%. This means that at least one vessel with ASFV-contaminated soybean meal would be imported once every 1563-21 years, respectively. When all raw corn was assumed to be contaminated (p0 = 100%), and no recontamination was assumed to occur (pR = 0%), the median probability of one vessel with ASFV-contaminated corn entering the United States was 2.02% (0.28%-9.43% 95% PI) or once every 50 years. Values of recontamination between 1% and 75% did not substantially change the risk of corn. Days of transport, virus survival during transport (D-value), and number of vessels shipped were the parameters most influential for increased likelihood of a vessel with ASFV-contaminated soybean meal or corn entering the United States. The model helped to identify knowledge gaps that are most influential on output values and serves as a framework that could be updated and parameterized as new scientific information becomes available. We propose that the quantitative risk assessment model developed in this study can be used as a framework for estimating the risk of ASFV entry into the United States and other ASFV-free countries through other types of imported feed ingredients that may potentially become contaminated. Ultimately, this model can be used to develop risk mitigation strategies and critical control points for inactivating ASFV during feed ingredient processing, storage, and transport, and contribute to the design and implementation of biosecurity measures to prevent the introduction of ASFV into the United States and other ASFV-free countries.